ADVANCE PROGRAM Mexico City Satellite Session

Transcription

1 2014 Mexico City Satellite Session ADVANCE PROGRAM 2014 International BigData Mexico City Satellite Session rd International Congress on Big Data (BigData) May 8, 2014 ITAM (Instituto Tecnologico Autonomo de Mexico) Río Hondo Campus 1 Rio Hondo St., Progreso Tizapan, Mexico City, D.F , Mexico Tel. +52 (55) Ext Topic: IEEE BigData 2014

2 Program Committee Chairs: Organization Committee J. Octavio Gutierrez-Garcia Department of Computer Science Instituto Tecnologico Autonomo de Mexico (ITAM), Mexico Victor M. Gonzalez Department of Computer Science Instituto Tecnologico Autonomo de Mexico (ITAM), Mexico Publicity Chair: Miguel Vargas Martin Faculty of Business and Information Technology University of Ontario Institute of Technology (UOIT), Canada Program Committee Members: Adrian Ramirez-Nafarrate, Instituto Tecnologico Autonomo de Mexico, Mexico Angel Kuri, Instituto Tecnologico Autonomo de Mexico, Mexico Emmanuel Lopez-Neri, Universidad del Valle de Mexico, Mexico Fernando Esponda, Instituto Tecnologico Autonomo de Mexico, Mexico Hector Orozco-Aguirre, Universidad Autonoma del Estado de Mexico, Mexico Jaime Zaragoza, Amazon, USA Jose Incera, Instituto Tecnologico Autonomo de Mexico, Mexico Luis Razo, Fysbee, France Luis-Felipe Rodriguez, Instituto Tecnologico de Sonora, Mexico Omar S. Gomez Gomez, Universidad Autonoma de Yucatan, Mexico Victor Landassuri-Moreno, Universidad Autonoma del Estado de Mexico, Mexico Pablo Vidales, RSA Seguros, Mexico Seokho Son, Gwangju Institute of Science and Technology, South Korea 2

3 IEEE BigData 2014 Mexico City Satellite Session Keynote Speakers Keynote 1: An Overview of Big Data Privacy Issues Patrick C. K. Hung, Faculty of Business and IT, University of Ontario Institute of Technology, Canada (05/08 Thursday, 9:00-9:45; Conference room) Abstract: Big data is the term for a collection of large and complex datasets from different sources that is difficult to process using traditional data management and processing applications. In these datasets, some information must be kept secret from others. On the other hand, some information has to be released for acquainting information or big data analytical services. The research challenge is how to protect the private information in the context of big data. Privacy is described by the ability to have control over the collection, storage, access, communication, manipulation and disposition of data. Some refer to privacy as the right for individuals to determine for themselves when, how, and to what extent information about them is communicated to others. Many countries set out legislations for how organizations may collect, use, or disclose personal information in the course of commercial activities. Failing to comply with these legislations, in their respective countries, may lead to civil and/or criminal penalties and/or imprisonment. In addition to the penalties, organizations may even suffer the loss of reputation and goodwill when the non-compliance of legislation is publicized. This talk will give an overview of privacy concepts and related research issues in big data applications, especially in health domain. About the Speaker: Patrick C. K. Hung is an Associate Professor at the Faculty of Business and Information Technology in University of Ontario Institute of Technology. Patrick has been worked with Boeing Research and Technology on aviation services-related research with a patent on mobile network dynamic workflow system. In addition, he is a Visiting Researcher at the University of Aizu at Fukushima in Japan, a Guest Professor in University of Innsbruck in Austria, University of Trento and University of Milan in Italy. Before that, he was a Research Scientist with Commonwealth Scientific and Industrial Research Organization in Australia. He is a founding committee member of the IEEE International Conference of Web Services, IEEE International Conference on Services Computing, and IEEE BigData Congress. He is an associate editor of the IEEE Transactions on Services Computing. Keynote 2: Studying Students Development of Misconceptions in Hybrid and Online Courses Miguel Vargas Martin, Faculty of Business and IT, University of Ontario Institute of Technology, Canada (05/08 Thursday, 10:15-11:00; Conference room) Abstract: This presentation will outline the state-of-the-art in online learning platforms. The speaker will also present a methodology for studying how learners develop misconceptions during the situated experience of teaching and learning as well as during the situated experience of cognitive and behavioral expression of what 3

4 has been learned during real-world applications. This methodology is being embedded into software-hardware platforms suitable for use by learning management systems (LMS) and massive open online courses (MOOCs). These types of platforms together constitute an educational environment we call the MISSED Misconception Instantiation as Students Study Educational Domains. MISSED can be used to assess learners conceptual and performance competencies in ways allowing cognitive and behavioral mapping that reveals patterns of misconception development. About the Speaker: Before joining the University of Ontario Institute of Technology (UOIT), he was a post-doctoral researcher at Alcatel Canada and Carleton University in Ottawa, Ontario. He is a licensed Professional Engineer in the Province of Ontario. His research focuses on two domains. First, he works in the area of providing security mechanisms to protect computer systems; under this umbrella, his major fields include new authentication paradigms and traffic inspection. A second research domain is the optimization of websites and virtual learning environments, where his work led to a freely available web service called Navdriver, and a learning platform prototype tested in real classroom settings at UOIT. He was the lead editor of IGI Global's Technology for Facilitating Humanity and Combating Social Deviations: Interdisciplinary Perspectives. Keynote 3: Mobile Solutions Helps PLM Achieve a Quantum Leap in its Operation Antonio Carrasco PLM Latina, Mexico (05/08 Thursday, 12:00-12:45; Conference room) Abstract: With the deployment of a mobile solution, PLM has achieved a quantum leap in its operational performance. Through this solution, PLM can now bring service applications for multiple device platforms to market rapidly, provide reliable data to clients regarding its products movement information, and deliver information to its business partners for better decision-making. In three years, 60 percent of PLM s total revenues have come from selling services digital platforms. PLM significantly increased its business by using IBM solutions to design and implement mobile applications in order to meet the growing demands of its customers, including physicians, pharmacists, hospitals, and laboratories. About the Speaker: Mr. Carrasco holds a master degree in Management by the London School of Economics and a Bachelor degree in Economics by the Instituto Tecnologico Autonomo de Mexico. He has over 15 year experience in strategy formation and execution, product and processes innovation for telecomm and publishing industries, banking services and government. He has developed state of the art electronic products and obtained, with Sociedad Hipotecaria Federal, the Hall of Fame award for Balanced Score Card Strategy Execution. He has been speaker and consultant for the World Bank, Interamerican Development Bank, Federal Reserve Bank, Secretaría de Relaciones Exteriores, within other government agencies in Mexico and Latin America. Actually, he is PLM CEO. 4

5 Keynote 4: Big Data & Analytics Sergio Reyes Hernández SAS, Mexico (05/08 Thursday, 12:45-13:30; Conference room) Abstract: Big data comes in all shapes and sizes and it can be stored in many forms. Decisions need to be made within seconds. For instance, credit approval must be made on the spot. With the explosion of Big Data problems, statistical learning has become a very hot field in many scientific areas as well as marketing, finance, and other business disciplines. People with statistical learning skills are in high demand. There are many choices to store your data. SAS works with many database partners in the marketplace. Whatever decision you make, the same fundamental principle applies: Operationalizing your data and analytics are paramount to making the right decision, at the right time, to the right customers. About the Speaker: Sergio Reyes has experience in analytical activities oriented to bank fraud detection and prevention; and also in the development of applications by making requirements analysis activities, relational models design and components codification. He also has wide knowledge on ETL processes generation and automation, and data cleansing; also on SAS Programming and data base generation and software development. Since 2011, he has worked at SAS developing statistics models and data mining, and on time series analysis for bank fraud detection and prevention. He has worked in companies such as MultiSoluciones Globales as a consultant, analyzing designing and implementing web applications, mainly of fiscal matter. He also worked at Softtek as a systems analyst where he implemented an academic management system for Universidad de las Américas, and a pension system for IMSS. Sergio has a degree on Computer Systems by Escuela Superior de Cómputo, of IPN; and he also studied Applied Mathematics and Computation at Facultad de Estudios Superiores Acatlán, of UNAM. 5

6 May 8 (Thursday), 2014 Time Keynote speech Keynote Speaker 9:00 9:45 An Overview of Big Data Privacy Issues Patrick C. K. Hung 10:15 11:00 Studying Students Development of Misconceptions in Hybrid and Online Courses Miguel Vargas Martin 12:00 12:45 Mobile Solutions Helps PLM Achieve a Quantum Leap in its Operation Antonio Carrasco 12:45 13:30 Big Data & Analytics Sergio Reyes Hernández Time 9:45 10:15 Research Track Session Session Chair: J.O. Gutierrez-Garcia Topic Big Data Infrastructure for analyzing data generated by Wireless Sensor Networks 11:00 11:30 Data Base Analysis using a Compact Data Set 11:30 12:00 The Babel File System 6

7 Research Track Session (05/08 Thursday) Session Chair: J.O. Gutierrez-Garcia 1. Big Data Infrastructure for analyzing data generated by Wireless Sensor Networks (#7237) Lídice García (Instituto Tecnologico Autonomo de Mexico) Jose Incera (Instituto Tecnologico Autonomo de Mexico) 2. Data Base Analysis using a Compact Data Set (#7009) Angel Kuri (Instituto Tecnologico Autonomo de Mexico) 3. The Babel File System (#7002) Moises Quezada Naquid (Universidad Autonoma Metropolitana) Ricardo Marcelín Jiménez (Universidad Autonoma Metropolitana) José Luis González Compeán (Cd. Valles Institute of Technology) Journal and Book Publications Extended versions of all presented and accepted papers will be invited for publication in the International Journal of Web Services Research (JWSR) which is indexed by SCI and EI or in the book "Big Data Applications and Use Cases" for the Springer International Series on Applications and Trends in Computer Science. The book will be indexed by Thomson Reuters SCI/EI. 7

8 Conference Venue Information The IEEE BigData 2014 Mexico Satellite Session will be held in Mexico City at ITAM (Instituto Tecnologico Autonomo de Mexico). Mexico City is one of the largest and oldest cities in Latin America as well as its most important political, cultural, educational and financial center. The city is part of an invaluable historic past Aztec, mixed with the magnificence of its churches and colonial palaces. The culture is present in the generous amount of museums and theaters. Mexico City offers a vast array of culinary experiences, entertainment and a wider variety of nightlife options. The satellite session will be held at ITAM Rio Hondo Campus, with address at: 1 Rio Hondo St., Progreso Tizapan, Mexico City, D.F , Mexico. You can arrive either from 1) Periférico or 2) Insurgentes, Revolución and Eje 10 Sur. 1) Arriving from Periférico: 8

9 2) Arriving from Insurgentes, Revolución and Eje 10 Sur 9